Multi Objective Optimization for Seismology (MOOS), with application to the Middle East, the Texas Gulf Coast, and the Rio Grande Rift.

dc.contributor.advisor

Pulliam, Robert Jay.

dc.creator

Agrawal, Mohit, 1985-

dc.date.accessioned

2016-06-21T16:19:12Z

dc.date.available

2016-06-21T16:19:12Z

dc.date.created

2016-05

dc.date.issued

2016-03-24

dc.date.submitted

May 2016

dc.identifier.uri

http://hdl.handle.net/2104/9653

dc.description.abstract

We develop and apply new modeling methods that make use of disparate but complementary seismic “functionals,” such as receiver functions and dispersion curves, and model them using a global optimization method called “Very Fast Simulated Annealing” (VFSA). We apply aspects of the strategy, which we call “Multi Objective Optimization for Seismology” (MOOS), to three broadband seismic datasets: a sparse network in the Middle East, a closely-spaced linear transect across Texas Gulf Coastal Plain, and a 2D array in SE New Mexico and West Texas (the eastern flank of the Rio Grande Rift). First, seismic velocity models are found, along with quantitative uncertainty estimates, for eleven sites in the Middle East by jointly modeling Ps and Sp receiver functions and surface (Rayleigh) wave group velocity dispersion curves. These tools demonstrate cases in which joint modeling of disparate and complementary functionals provide better constraints on model parameters than a single functional alone. Next, we generate a 2D stacked receiver function image with a common conversion point stacking technique using seismic data from a linear array of 22 broadband stations deployed across Texas’s Gulf Coastal Plain. The image is migrated using velocity models found by modeling dispersion curves computed via ambient noise cross-correlation. Our results show that the Moho disappears outboard of the Balcones Fault Zone and that a significant, negative-polarity discontinuity exists beneath the Coastal Plain. Lastly, we stack and depth-migrate Ps and Sp receiver functions computed from data recorded by broadband stations deployed by the SIEDCAR (Seismic Investigation of Edge Driven Convection Association with Rio Grande Rift) project. To find P-and Swave velocity models for receiver function migration, we develop and apply a technique that is analogous to “velocity analysis” in seismic reflection processing. The resulting 3D image reveals gaps in the seismically-determined lithosphere-asthenosphere boundary (LAB) and Moho beneath dramatically uplifted topography and above a distinct fast anomaly (found independently via seismic travel time tomography). We speculate that this gap is the result of large-scale lithospheric removal associated with east-west extension and the northward propagation of the Rio Grande Rift.

dc.format.mimetype

application/pdf

dc.language.iso

en

dc.subject

Time-series analysis. Inverse theory. Geophysics.

dc.title

Multi Objective Optimization for Seismology (MOOS), with application to the Middle East, the Texas Gulf Coast, and the Rio Grande Rift.